• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.1
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• pp.464-469
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• 2013

After city of Busan has been entered to the aging society in 2000, the city has the highest aging rate among 7 representative cities in 2011. Moreover, while entire population and number of average household are decreasing, over 65 years old of elderly population is rapidly increasing. So, it is possible to enter the super-aged society, where aging rate would be about 20% after 2020. The purpose of this study is that older housing-related analysis is consisted of dong-unit, and this led microscopic analysis has become necessary. Surveys from 2000 through 2010, census aggregate (output area) unit of spatial analysis was conducted. Take advantages of this, aging population and area, soaring area, high-density areas, such as the region of interest were primary extracted, and microscopic location and spatial distribution patterns were analyzed. Upon analysis, aging population is concentrated in the city and adjacent area, the highlands, and 10 years of increasing rate was more than 30 times in certain aggregate. Regarding the characteristic of these areas, the original city center, Busan, especially concentrated and intensified in aging population. Also, 2000 to 2010, the overall distribution pattern of Busan has identified aging population that is increasingly being distributed. This is the result, which is confronted with previous research result. Entering a super aged-society for the future is accordance with migration of social costs and improve the quality of life of elderly. And this could be the basic information to use the spatial dimension for the corresponding.

• Journal of Internet Computing and Services
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• v.10 no.5
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• pp.65-78
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• 2009

The most commonly adopted approach to find valuable information from tree data is to extract frequently occurring subtree patterns from them. Because mining frequent tree patterns has a wide range of applications such as xml mining, web usage mining, bioinformatics, and network multicast routing, many algorithms have been recently proposed to find the patterns. However, existing tree mining algorithms suffer from several serious pitfalls in finding frequent tree patterns from massive tree datasets. Some of the major problems are due to (1) modeling data as hierarchical tree structure, (2) the computationally high cost of the candidate maintenance, (3) the repetitious input dataset scans, and (4) the high memory dependency. These problems stem from that most of these algorithms are based on the well-known apriori algorithm and have used anti-monotone property for candidate generation and frequency counting in their algorithms. To solve the problems, we base a pattern-growth approach rather than the apriori approach, and choose to extract maximal frequent subtree patterns instead of frequent subtree patterns. The proposed method not only gets rid of the process for infrequent subtrees pruning, but also totally eliminates the problem of generating candidate subtrees. Hence, it significantly improves the whole mining process.

• The Journal of Bigdata
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• v.7 no.1
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• pp.15-27
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• 2022

In the past five years, the fatality rate of single-vehicle accidents has been 4.7 times higher than that of all accidents, so it is necessary to establish a system that can detect and respond to single-vehicle accidents immediately. The IoT(Internet of Thing)-based real-time traffic accident recognition system proposed in this study is as following. By attaching an IoT sensor which detects the impact and vehicle ingress to the guardrail, when an impact occurs to the guardrail, the image of the accident site is analyzed through artificial intelligence technology and transmitted to a rescue organization to perform quick rescue operations to damage minimization. An IoT sensor module that recognizes vehicles entering the monitoring area and detects the impact of a guardrail and an AI-based object detection module based on vehicle image data learning were implemented. In addition, a monitoring and operation module that imanages sensor information and image data in integrate was also implemented. For the validation of the system, it was confirmed that the target values were all met by measuring the shock detection transmission speed, the object detection accuracy of vehicles and people, and the sensor failure detection accuracy. In the future, we plan to apply it to actual roads to verify the validity using real data and to commercialize it. This system will contribute to improving road safety.

• Journal of the Korean Society for information Management
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• v.33 no.2
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• pp.157-176
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• 2016

Cited-by Linking Service is one of the CrossRef's information services that allows you to discover how your publications are being cited and to incorporate that information into your online publication platform. This study tries to investigate citation patterns in the field of both Natural Science and Engineering using all of DOI assigned articles and Cited-by Linking data which are accumulated and managed by KISTI. The investigating approach is designed to verify the theory of 1) cognitive accessibility, 2) 'perceived quality and significance' and 3) 'subject relativity'. For cognitive accessibility verification the fulltext language portion of Korean and English between "Cited DOI Source Data" and "NOT Cited DOI Source Data" was compared. For perceived quality and significance verification the availability of the "Cited DOI Source Data" and "NOT Cited DOI Source Data" from SCIE and SCOPUS was employed. For subject relativity DOI data were classified and analysed on the basis of OECD subject classification scheme. Findings are that global citability is closely related to the fulltext language of the articles and their quality and significance. And in the natural science field most of citations are from the same subject categories, while relatively more citations are from other subject categories in the engineering field.

• Journal of the Korea Society of Computer and Information
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• v.16 no.12
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• pp.285-296
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• 2011

UN, OECD, ITU and other international organizations regularly announce ISI (Information Society Index) to utilize in establishing and evaluating information policies. ISI is utilized as important data for countries to evaluate their information policy performance and select future projects. As the advancement of information systems, the importance of information security has been emerged. Accordingly, NISI (National Information Security Index) has been required. NISI number is the most clearly figure to express the characteristics of a particular group's information security. It can be utilized in determining information security policies. Currently, questionnaire method has been used to calculate NISI number. But there is an absolute lack of statistical data, and the reliability of surveyed statistical data is problematic. The objective of this paper is to show how to collect precise micro data of each company's information security index numbers, and to develop an OLAP database system which calculating NISI numbers by using those micro data. In this process of the survey, we presented the technique to collect the data more systematically, and to analyze the data without using questionnaire method. OLAP architecture performs only well on the facts that are summarizable along each dimension, where all hierarchy schemas are distributive. Therefore we transformed the non-distributive hierarchy schema into the distributive hierarchy schema to implement OLAP database system. It is thought that this approach will be useful one from an implementation and schema design point of view.

• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.1-15
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• 2024

The construction of smart communities is a new method and important measure to ensure the security of residential areas. In order to solve the problem of low accuracy in face recognition caused by distorting facial features due to monitoring camera angles and other external factors, this paper proposes the following optimization strategies in designing a face recognition network: firstly, a global graph convolution module is designed to encode facial features as graph nodes, and a multi-scale feature enhancement residual module is designed to extract facial keypoint features in conjunction with the global graph convolution module. Secondly, after obtaining facial keypoints, they are constructed as a directed graph structure, and graph attention mechanisms are used to enhance the representation power of graph features. Finally, tensor computations are performed on the graph features of two faces, and the aggregated features are extracted and discriminated by a fully connected layer to determine whether the individuals' identities are the same. Through various experimental tests, the network designed in this paper achieves an AUC index of 85.65% for facial keypoint localization on the 300W public dataset and 88.92% on a self-built dataset. In terms of face recognition accuracy, the proposed network achieves an accuracy of 83.41% on the IBUG public dataset and 96.74% on a self-built dataset. Experimental results demonstrate that the network designed in this paper exhibits high detection and recognition accuracy for faces in surveillance videos.

• Journal of Korean Society of Transportation
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• v.33 no.1
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• pp.14-28
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• 2015

Numerous research has been conducted using internet search data since the mid-2000s. For example, Google Inc. developed a service predicting influenza patterns using the internet search data. The main objective of this study is to prove the hypothesis that highway traffic indices are similar to the internet search patterns. In order to achieve this objective, a model to predict the number of vehicles entering the expressway and space-mean speed was developed and the goodness-of-fit of the model was assessed. The results revealed several findings. First, it was shown that the Google search traffic was a good predictor for the TCS entering traffic volume model at sites with frequent commute trips, and it had a negative correlation with the TCS entering traffic volume. Second, the Naver search traffic was utilized for the TCS entering traffic volume model at sites with numerous recreational trips, and it was positively correlated with the TCS entering traffic volume. Third, it was uncovered that the VDS speed had a negative relationship with the search traffic on the time series diagram. Lastly, it was concluded that the transfer function noise time series model showed the better goodness-of-fit compared to the other time series model. It is expected that "Big Data" from the internet search data can be extensively applied in the transportation field if the sources of search traffic, time difference and aggregation units are explored in the follow-up studies.

• Journal of the Korea Society of Computer and Information
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• v.17 no.2
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• pp.149-157
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• 2012

In this thesis, the problem of computing approximate answers to continuous sliding-window joins over data streams when the available memory may be insufficient to keep the entire join state. One approximation scenario is to provide a maximum subset of the result, with the objective of losing as few result tuples as possible. An alternative scenario is to provide a random sample of the join result, e.g., if the output of the join is being aggregated. It is shown formally that neither approximation can be addressed effectively for a sliding-window join of arbitrary input streams. Previous work has addressed only the maximum-subset problem, and has implicitly used a frequency based model of stream arrival. There exists a sampling problem for this model. More importantly, it is shown that a broad class of applications for which an age-based model of stream arrival is more appropriate, and both approximation scenarios under this new model are addressed. Finally, for the case of multiple joins being executed with an overall memory constraint, an algorithm for memory allocation across the join that optimizes a combined measure of approximation in all scenarios considered is provided.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.12
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• pp.1281-1286
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• 2015

Fatigue cracks can be generated in aircraft as a result of the cumulative time spent during flight operations, which can extend for long periods of time and cover a variety of missions. If a crack occurs in an aircraft's main spar, it can generate many problems, including a lift time reduction. To solve this problem, it was necessary to perform an analysis of fatigue crack growth in the fatigue critical locations. Much time and expense is involved in generating the stress needed for a crack propagation analysis over a long period of time to obtain the amount of data required for an actual aircraft. In this paper, an algorithm is developed that can calculate the spectrum of stress over a long period of time for a mission by the Southwest Research Institute, which is based on the short-time load factor data produced using the peak-valley cycle counting method.

• Archives of design research
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• v.16 no.3
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• pp.59-70
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• 2003

The consumer's feelings toward products is each evaluated and appears in different way that is to say there are various types of motives for deciding a purchase for example, there might be an interesting function and emotional reaction. How is the product image that induces motives like this metaphorized and evaluated to be existing in the mental image. This study inquired into, it by presenting problems conscious of both sides indicated above, the major points associated with image of the product, characteristic positions of product elements and evaluation of the product. To draw out a clear conclusion, first three hypotheses were established and case a study was performed as part of conclusive research for verification of this. The collected data was made, by simple tabulation to represent the overall flow, and based on this, concrete analysis was conducted on the three reserch items. The analysis method weighted on quantitative analysis with consideration to consumer's psychological aspect. As the result, three important conclusions could be drawn out or ratiocination for evaluation of mental image formation.